Triple
T35959414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Storm of 1913 |
E1039954
|
entity |
| Predicate | hardestHitArea |
P97584
|
FINISHED |
| Object | southern and central Lake Huron |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: southern and central Lake Huron | Statement: [Great Storm of 1913, hardestHitArea, southern and central Lake Huron]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hardestHitArea Context triple: [Great Storm of 1913, hardestHitArea, southern and central Lake Huron]
-
A.
hardestHitRegion
chosen
Indicates the region that experienced the greatest impact or severity compared to all other regions.
-
B.
hasLargestAreaOf
Indicates that the subject entity possesses the greatest area (size of surface or region) compared to the other entities in the specified set or context.
-
C.
hardestShotSpeedMph
Indicates the maximum recorded speed, in miles per hour, of the hardest shot taken.
-
D.
hitOver
Indicates that one entity strikes or impacts another entity by moving over or across it.
-
E.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:07 p.m.